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Data Compression and Decompression
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Data Compression and Decompression

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Questions and Answers

What is one of the advantages of compression in terms of disk space?

  • Keep disk space usage the same
  • Use more disk space
  • Use less disk space (correct)
  • Increase disk space needed
  • Why do large search engines keep a significant part of the postings in memory?

  • To slow down the search process
  • Because compression lets you keep more in memory (correct)
  • Because compression is not possible
  • To increase disk space usage
  • What is the main advantage of decompression algorithms?

  • They are fast (correct)
  • They are not used in IR
  • They are not useful
  • They are slow
  • What is the approximate number of documents in Reuters RCV1?

    <p>800,000</p> Signup and view all the answers

    What is the purpose of compression in dictionaries?

    <p>To make them smaller and fit in main memory</p> Signup and view all the answers

    What is the benefit of compression in terms of data transfer?

    <p>It is faster than reading uncompressed data</p> Signup and view all the answers

    What is the average number of tokens per document in Reuters RCV1?

    <p>200</p> Signup and view all the answers

    Why is compression useful in information retrieval?

    <p>It saves a little money and gives users more space</p> Signup and view all the answers

    What type of compression preserves all information?

    <p>Lossless compression</p> Signup and view all the answers

    What is the primary purpose of dictionary compression?

    <p>To reduce storage space</p> Signup and view all the answers

    Which of the following preprocessing steps can be viewed as a form of lossy compression?

    <p>All of the above</p> Signup and view all the answers

    What is the relationship between vocabulary size and collection size?

    <p>Vocabulary size increases with collection size</p> Signup and view all the answers

    What is the main focus of the compression chapter in this course?

    <p>Basic Boolean index compression</p> Signup and view all the answers

    What is the approximate number of different words of length 20?

    <p>7020</p> Signup and view all the answers

    What is the benefit of pruning postings entries in Chapter 7?

    <p>Almost no loss of quality in top k list</p> Signup and view all the answers

    How many bytes are required to store each term in the postings?

    <p>7.5</p> Signup and view all the answers

    What is the purpose of storing the dictionary as a string?

    <p>To save up to 60% of dictionary space</p> Signup and view all the answers

    How many bytes are required to resolve 3.2M positions?

    <p>3 bytes</p> Signup and view all the answers

    What is the average number of bytes per term in the term string?

    <p>8 bytes</p> Signup and view all the answers

    What is the total space required for the dictionary using the fixed width approach?

    <p>11.2 MB</p> Signup and view all the answers

    What is the purpose of blocking in the context of dictionary compression?

    <p>To store pointers to every kth term string</p> Signup and view all the answers

    How many extra bytes are required to store term lengths in blocking?

    <p>1 byte</p> Signup and view all the answers

    What is the net effect of blocking on the dictionary space?

    <p>Save 9 bytes and lose 4 bytes on term lengths</p> Signup and view all the answers

    What is the total space required for the dictionary using the dictionary-as-a-string approach?

    <p>7.6 MB</p> Signup and view all the answers

    What is the main idea behind front-coding in dictionary compression?

    <p>Storing only the differences between sorted words</p> Signup and view all the answers

    How does the blocking technique with k = 4 reduce the size of the dictionary?

    <p>By reducing the number of blocks in the dictionary</p> Signup and view all the answers

    What is the main goal of postings compression?

    <p>To store each posting compactly</p> Signup and view all the answers

    How many bits are required to represent a docID in Reuters (800,000 documents) using 4-byte integers?

    <p>32 bits</p> Signup and view all the answers

    What is the approximate number of bits required to represent a docID in Reuters (800,000 documents) using logarithmic compression?

    <p>20 bits</p> Signup and view all the answers

    What is the term for a posting in the context of information retrieval?

    <p>A document ID</p> Signup and view all the answers

    What is the ratio of the size of the postings file to the size of the dictionary?

    <p>At least 100:1</p> Signup and view all the answers

    What is the main conflict in postings compression?

    <p>Storing rare terms compactly vs. storing common terms compactly</p> Signup and view all the answers

    What is the optimal prefix code when P(n) = 2–n?

    <p>Gamma code</p> Signup and view all the answers

    What is the purpose of the Gamma code?

    <p>To compress better with bit-level codes</p> Signup and view all the answers

    How is the offset represented in the Gamma code?

    <p>As a binary number with the leading bit cut off</p> Signup and view all the answers

    What is the length in the Gamma code of the number 13?

    <p>3</p> Signup and view all the answers

    What is the Gamma code of the number 13?

    <p>1110101</p> Signup and view all the answers

    What is the bitwise operator used for extracting 7 bits from a number?

    <p>&amp; (bitwise and)</p> Signup and view all the answers

    What is the purpose of the bitwise right shift operator?

    <p>To extract a certain number of bits from a number</p> Signup and view all the answers

    What is the Python syntax for a bitwise right shift operator?

    <p>&gt;&gt;</p> Signup and view all the answers

    Study Notes

    Compression in Information Retrieval

    • Compression is useful in IR to reduce disk space, save money, and increase speed.
    • Decompression algorithms are fast, making compression a viable option.

    Why Compression for Inverted Indexes?

    • Dictionary compression: Make the dictionary small enough to fit in main memory, allowing for faster querying.
    • Postings file compression: Reduce disk space needed and decrease the time needed to read postings lists from disk.

    Reuters RCV1 Statistics

    • Number of documents: 800,000
    • Average number of tokens per document: 200
    • Number of terms (word types): approximately 400,000
    • Average number of bytes per token: 6 (including spaces and punctuation), 4.5 (excluding spaces and punctuation)
    • Average number of bytes per term: 7.5
    • Number of non-positional postings: 100,000,000

    Lossless vs. Lossy Compression

    • Lossless compression: All information is preserved, typically used in IR.
    • Lossy compression: Discard some information, used in preprocessing steps like case folding, stop words, stemming, and number elimination.

    Vocabulary Size vs. Collection Size

    • The term vocabulary size grows with the collection size, especially with Unicode.
    • Vocabulary size is important for compression, as it affects the size of the dictionary.

    Compression Schemes

    • Compression can be applied to the dictionary and postings files.
    • Basic Boolean index compression is a starting point, but can be extended to positional indexes.

    Dictionary Compression

    • Dictionary compression is important to reduce disk space and make querying faster.
    • Techniques: store dictionary as a string, blocking, and front coding.

    Dictionary-as-a-String

    • Store dictionary as a long string of characters, with pointers to mark the end of each word.
    • This can save up to 60% of dictionary space.

    Blocking

    • Store pointers to every kth term string, reducing the number of pointers needed.
    • Term lengths need to be stored, adding an extra byte.

    Front Coding

    • Front-coding: store differences between sorted words, taking advantage of common prefixes.
    • This is similar to general string compression.

    RCV1 Dictionary Compression Summary

    • Fixed width: 11.2 MB
    • Dictionary-as-String with pointers to every term: 7.6 MB
    • Dictionary-as-String with blocking (k=4): 7.1 MB
    • Dictionary-as-String with blocking and front coding: 5.9 MB

    Postings Compression

    • Postings compression is important because the postings file is much larger than the dictionary.
    • Goal: store each posting compactly, using fewer than 20 bits per docID.

    Postings: Two Conflicting Forces

    • Store rare postings (e.g., arachnocentric) using fewer bits, but more frequent postings need more bits.
    • Optimal solution: use log2 P(n) bits, where P(n) is the probability of the posting.

    Gamma Codes

    • Gamma codes are a type of bit-level code that can compress better than other methods.
    • Represent a gap G as a pair of length and offset, where offset is G in binary with the leading bit cut off.
    • Length is the length of the offset, encoded with unary code.

    Gamma Code Examples

    • Examples of gamma codes for various numbers, showing the length and offset.

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    Quiz Team

    Description

    Understand the benefits and principles of data compression and decompression, including saving disk space and increasing speed.

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